Rake receiver and de-spreading method thereof

ABSTRACT

The invention relates to a rake receiver and a method for de-spreading thereof. A plurality of noise branches is adopted for producing a plurality of noise components in the rake receiver. Next, a noise combining unit adjusts each noise component according to a plurality of noise weights, so as to combine the noise components to obtain an interference-plus-noise estimation value. The rake receiver eliminates the noises in the main signal generated by the signal branches through using the interference-plus-noise estimation value. Therefore, the performance of a receiving terminal can be enhanced.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of Taiwan applicationserial no. 96123507, filed on Jun. 28, 2007. The entirety of theabove-mentioned patent application is hereby incorporated by referenceherein and made a part of this specification.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a rake receiver. More particularly, thepresent invention relates to a rake receiver using channel estimation.

2. Description of Related Art

Wireless communication system uses radio waves to transmit messages.During the process of transmitting electric waves, the electric wavesare affected by buildings or automobiles in the environment, so signalsfrom a transmitting terminal finally reach a receiving terminal afterpassing through various different reflection or refraction paths, andthe time for the signal reaches the receiving terminal varies dependingupon a different path. Therefore, the wireless communication environmentis considered as a multi-path channel. From a perspective ofmathematics, it is assumed that the signal transmitted from thetransmitting terminal at the time t is expressed as s(t), the receivedsignal r(t) received by the receiving terminal at the time t may beexpressed the following equation:

$\begin{matrix}{{r(t)} = {{\sum\limits_{l = 0}^{L - 1}\; {h_{l}{s\left( {t - \tau_{l}} \right)}}} + {{n(t)}.}}} & (1)\end{matrix}$

In the Equation (1), L is the number of paths, τ₁ is the path delay timecaused by the l^(th) path in L transmission paths, h_(l) is the channelgain of the l^(th) path in L transmission paths, and n(t) is the channelnoise.

In the current communication system, a rake receiver is usually used inthe receiving terminal, a plurality of branches (also called a pluralityof fingers) therein is used to collect signals in different paths, so asto resist the signal attenuation caused by the multi-path channel. Amongthe current applications, the rake receiver is most commonly used in thecode division multiple access (hereafter referred to as CDMA) system.FIG. 1 is a systematic block diagram of a rake receiver in a CDMAsystem.

Referring to FIG. 1, the rake receiver 100 includes a plurality offingers 110_0-110_(L−1) and a combiner 140. The received signal r(t) isrespectively input to delay units 120_0-120_(L−1) in the fingers110_0-110_(L−1); and the delay units 120_0-120_(L−1) respectively delaythe received signal r(t) for a time τ₀-τ_(L-1) and then output it tode-spreaders 130_0-130_(L−1). Then, the de-spreaders 130_0-130_(L−1) areused to respectively generate signal components y(τ₀)-y(τ_(L-1)) forbeing output to the combiner 140. Upon receiving the signal componentsy(τ₀)-y(τ_(L-1)) output by the fingers 110_0-110_(L−1), the combiner 140makes the received signal components y(τ₀)-y(τ_(L-1)) be respectivelymultiplied by a weight w₀*-w_(L-1)*, and then summed up, and outputs ade-spreading signal {circumflex over (x)}.

The number of the fingers 110_0-110_(L−1) is designed to be the numberof the paths, the time τ₀-τ_(L-1) in the delay units 120_0-120_(L−1) arethe path delay time on each path obtained after the receiving terminalhas performed the channel estimation, and the weights w₀*-w_(L-1)* inthe combiner 140 are the conjugate of channel gains on each pathobtained after the receiving terminal has performed the channelestimation. That is to say, in the practical application, the rakereceiver 100 of the receiving terminal sets each finger 110_0-110_(L−1)according to the channel estimation result, so as to collect signals ofeach path from the channel.

In the practical transmission, the CDMA system uses a plurality ofspreading codes to transmit a plurality of user' signals at the sametime, and uses the orthogonality between each spreading code to preventthe signals between the users from interfering with each other.Therefore, when the signal is interfered by the multi-path in thechannel, the orthogonality between the spreading codes is also damaged,as a result, the signals between the users are mutually interfered, thatis, multiple-user interference (MUI). In addition, the interference ofthe multi-path also causes inter-symbol interference (ISI) for the sameuser. However, the conventional rake receiver only considers theattenuation of the signals caused by the multi-path channel, but cannotovercome the MUI and the ISI problems.

From the perspective of mathematics, the conventional rake receiverassumes the noises n(t) in the channel as a white Gaussian noise, andonly processes the signal attenuation caused by the multi-path (that is,only the path delay time τ₀-τ_(L-1) and the channel gains h₀-h_(L-1) ofthe multi-path channel are considered). However, during the practicalchannel transmission, due to the MUI and the ISI, the noises n(t) in thechannel are not the white Gaussian noise, but colored Gaussian noise.Therefore, the conventional rake receiver ignores the MUI and the ISI,such that the performance of the receiving terminal becomes relativelypoor, and meanwhile the bit error rate of the signals demodulated by thereceiving terminal becomes relatively large.

Recently, in order to solve the attenuation of the multi-path channeland to reduce the interference of the colored Gaussian noise of thechannel, a US patent (Note [1]) and a paper (Note [2]) have proposed ageneralized RAKE (hereafter referred to as G_RAKE) receiver. FIG. 2 is asystematic block diagram of a G-RAKE receiver in a CDMA system.

Referring to FIG. 2, a G-RAKE receiver 200 includes a plurality offingers 210_0-210_(J−1) and a combiner 240. The architecture of theG_RAKE receiver 200 is similar to the rake receiver 100 in FIG. 1,except that the number of the fingers 210_0-210_(J−1) of the G-RAKEreceiver 200 is J. and the value J is greater than the number of thepaths L. Each time d₀-d_(J-1) in the delay units 210_0-210_(J−1) doesnot necessarily correspond to the path delay time on the transmissionpath, but designed by utilizing a statistical value of the maximumsignal-to-noise ratio (SNR).

In addition, the weights w₀*-w_(J-1)* in the combiner 240 are calculatedby using the maximum likelihood (ML) rule. The w₀*-w_(J-1)* can berepresented by a vector w, and the value of w₀*-w_(J-1)* is calculatedaccording to w=R_(u) ⁻¹h_(J), in which the superscript (−1) representsthe matrix inversion operation. h_(J) is the channel gain acquiredthrough channel estimation. R_(u) is a J×J matrix, in which thecalculation process for each element value therein has been illustratedin the documents of Note [1] and the Note [2]. R_(u) is defined as acovariance matrix of the vector u, and the elements in the vector u arenoises included in the signal output from each finger of the G-RAKEreceiver.

In the document of Note [2], it is illustrated that the number J of thefingers of the G-RAKE receiver is greater than the number L of the pathsof the channel, which aims at making a part of the fingers match withthe paths in the channel, so as to collect the signal of each path, andalso aims at making the remaining fingers (that is, the inner delay timenot equal to the path delay time of the multi-path channel) whiten thecolored Gaussian noises in the channel. Therefore, the G-RAKE receivercan solve the attenuation of the multi-path channel and can reduce theinterference of the colored Gaussian noise of the channel.

Although the G-RAKE receiver makes the receiving terminal haverelatively desirable performance, the dimension of R_(u) is J×J, suchthat a large amount of calculations is required when the inverseoperation of the matrix R_(u) is performed. In addition, the timed₀-d_(J-1) designed through maximizing SNR also requires a considerablyamount of calculations.

Note [1]: US Patent Publication No. US 2006/0188007 A1.

Note [2]: G. E. Bottomley, T. Ottosson, and Yi-Pin Eric Wang, “AGeneralized RAKE Receiver for Interference Suppression”, IEEE J. select.Areas Commun., vol. 18, pp. 1536-1545, August 2000.

SUMMARY OF THE INVENTION

Accordingly, the present invention is directed to a rake receiver forreducing the bit error rate of a signal demodulated by a receivingterminal, and meanwhile effectively reducing a complexity of thereceiving terminal.

The present invention is also directed to a data demodulation method forestimating and eliminating noises and interference in the receivedsignal under a condition of low complexity.

The present invention provides a rake receiver, which includes a channelestimation module, L signal branches, I noise branches, and a combiner.The channel estimation module estimates a plurality of path delay timesand corresponding channel gains in the multi-path channel. L signalbranches respectively delay the received signal for a plurality ofchannel path delay times to obtain a plurality of delayed receivedsignals, and respectively de-spread each delayed received signal tooutput a plurality of signal components. I noise branches respectivelydelay the received signal for a plurality of preset times to obtain aplurality of delayed noise signals, and respectively de-spread eachdelayed noise signal to output a plurality of noise componentsrespectively. The combiner first combines the signal components togenerate a main signal, and combines the noise components to generate aninterference-plus-noise estimation value, and further outputs ade-spreading signal according to a difference value between the mainsignal and the interference-plus-noise estimation value. The combineradjusts weights of the plurality of signal components in the main signalaccording to the channel gains, and adjusts weights of the plurality ofnoise components in the interference-plus-noise estimation valueaccording to I noise weights.

In an embodiment of the present invention, taking the i^(th) signalbranch among the L signal branches as an example, it includes a delayunit and a de-spreader. The delay unit delays the received signal for ani^(th) channel path delay time to output an i^(th) delayed receivedsignal to the de-spreader. The de-spreader convolves the i^(th) delayedreceived signal with a local spreading waveform, and samples theconvolved result to an i^(th) signal component. Taking the j^(th) noisebranch among the I noise branches as an example, it includes a delayunit and a de-spreader. The delay unit delays the received signal for aj^(th) preset time to output a j^(th) delayed noise signal to thede-spreader. The de-spreader convolves the j^(th) delayed noise signalwith a local spreading waveform, and samples the convolved result to aj^(th) noise component.

In an embodiment of the present invention, the combiner includes asignal combining unit, a noise combining unit, and an adder. The signalcombining unit combines a plurality of signal components according to Lsignal weights to generate and output the main signal, in which the Lsignal weights are obtained according to the channel gains of themulti-path channel. The noise combining unit combines a plurality ofsignal components according to I signal weights to generate and outputthe interference-plus-noise estimation value. The adder subtracts theinterference-plus-noise estimation value from the main signal to outputa de-spreading signal.

In an embodiment of the present invention, the plurality of signalweights is represented as A₀-A_(L-1), and a signal weight vector formedby a conjugate value of the signal weights A₀-A_(L-1) is represented asα=[A₀*, . . . , A_(L-1)*]^(T). The plurality of noise weights isrepresented as B₀-B_(I-1), and a noise weight vector formed by aconjugate value of the noise weights B₀-B_(I-1) is represented asβ=[B₀*, . . . , B_(I-1)*]^(T). In an embodiment of the presentinvention, the rake receiver further includes a noise weight calculatingunit. The noise weight calculating unit calculates the noise weightsB₀-B_(I-1) through a noise matrix R_(u) and an equation β=R_(n)⁻¹R_(ns)α, and outputs them to the noise combining unit, in which R_(u)is a covariance matrix of a noise vector u, with a dimension of(I+L)×(I+L), and the noise vector u is the noise in the signals outputfrom the plurality of signal branches and the plurality of noisebranches, with a length of I+L. The matrix R_(n) is a I×I sub-matrix ata bottom right corner of the noise matrix R_(u), the matrix R_(ns) is aI×L sub-matrix at a bottom left corner of the noise matrix R_(u), inwhich the superscript (−1) represents an inverse matrix operation.

In an embodiment of the present invention, the rake receiver furtherincludes a noise branch selecting unit, which is used to select first Icandidates having larger metrics from a plurality of candidates, toserve as the I preset times. The metric is |β_(i)|²E[|z_(n)(m_(i))|²],the i^(th) candidate corresponds to the i^(th) preset time m_(i), thei^(th) noise branch generates the i^(th) noise component z_(n)(m_(i))according to the i^(th) preset time m_(i), β_(i)is a conjugate value ofthe noise weight corresponding to the i^(th) noise componentz_(n)(m_(i)), and E[•] represents an expected value operation.

The present invention further provides a de-spreading method, whichincludes the following steps: estimating a plurality of channel gainsand a plurality of corresponding path delay times in the multi-pathchannel; receiving a received signal from the multi-path channel;delaying the received signal for a plurality of channel path delay timesrespectively to obtain a plurality of delayed received signals, andde-spreading the delayed received signals respectively to generate aplurality of signal components; delaying the received signal for aplurality of preset times respectively to obtain a plurality of delayednoise signals, and de-spreading the delayed noise signals respectivelyto obtain a plurality of noise components; adjusting weights of theplurality of signal components in a main signal respectively accordingto the channel gains, so as to combine the signal components to obtainthe main signal; adjusting weights of the plurality of noise componentsin an interference-plus-noise estimation value according to a pluralityof noise weights, so as to combine the noise components to obtain theinterference-plus-noise estimation value; and generating a de-spreadingsignal according to a difference between the main signal and theinterference-plus-noise estimation value.

In an embodiment of the present invention, the step of generating theplurality of signal components includes: delaying the received signalfor an i^(th) channel path delay time to obtain an i^(th) delayedreceived signal; and then convolving the i^(th) delayed received signalwith a local spreading waveform, and sampling the convolved result as ani^(th) signal component. The step of generating the plurality of noisecomponents includes: delaying the received signal for an i^(th) presettime to obtain an i^(th) delayed noise signal; and then convolving thei^(th) delayed noise signal with a local spreading waveform, andsampling the convolved result to an i^(th) noise component.

In an embodiment of the present invention, the step of combining to formthe main signal includes: generating a plurality of signal weightsaccording to the plurality of channel gains; multiplying the i^(th)signal component by an i^(th) signal weight, so as to generate an i^(th)product; and adding up the above products to obtain the main signal. Thestep of combining to form the interference-plus-noise estimation valueincludes: multiplying an i^(th) noise component by an i^(th) noiseweight to generate an i^(th) product; and adding up the plurality ofproducts to obtain the interference-plus-noise estimation value.

In an embodiment of the present invention, the number of the signalcomponents is L, and the number of the noise components is I. The signalweights are represented as A₀-A_(L-1), and a signal weight vector formedby a conjugate value of the signal weights A₀-A_(L-1) is represented asα=[A₀*, . . . , A_(L-1)]^(T). The noise weights are represented asB₀-B_(I-1), and a noise weight vector composed of a conjugate value ofthe noise weights B₀-B_(I-1) is represented as β=[B₀*, . . . ,B_(I-1)]^(T). In an embodiment of the present invention, thede-spreading method further includes calculating a I×I sub-matrix at abottom right corner of a noise matrix R_(u) to obtain a matrix R_(n), inwhich R_(u) is a covariance matrix of a noise vector u, with a dimensionof (I+L)×(I+L), and the noise vector u is formed by the noise in thesignals components and the noise components, with a length of I+L;calculating a I×L sub-matrix at a bottom left corner of the noise matrixR_(u) to obtain a matrix R_(ns); calculating an inverse matrix of thematrix R_(n) to obtain a matrix R_(n) ⁻¹, wherein the superscript (−1)represents an inverse matrix operation; and using an equation β=R_(n)⁻¹R_(ns)α to calculate the noise weights B₀-B_(I-1).

In an embodiment of the present invention, the de-spreading methodfurther includes: calculating a metric of an i^(th) candidate among aplurality of candidates; and selecting first I candidates having largermetrics to serve as the I preset times, in which the metric is|β_(i)|²E[|z_(n)(m_(i))|²], the i^(th) candidate corresponds to thei^(th) preset time m_(i), the i^(th) preset time m_(i) corresponds tothe i^(th) noise component z_(n)(m_(i)), β_(i) is a conjugate value ofthe noise weight corresponding to the i^(th) noise component, and E[•]represents an expected value operation.

The present invention uses an interference-plus-noise estimation valuegenerated by the plurality of noise branches and the noise combiningunit to eliminate the noises in the main signal, so as to lower the biterror rate. In addition, in the present invention, when the noise weightis calculated, it is only necessary to calculate the inverse matrix ofthe sub-matrix R_(n) in the noise matrix R_(u), and thereby reducing theoperations at the receiving terminal.

In order to make the aforementioned and other objects, features andadvantages of the present invention comprehensible, preferredembodiments accompanied with figures are described in detail below.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary, and are intended toprovide further explanation of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate embodiments of theinvention and, together with the description, serve to explain theprinciples of the invention.

FIG. 1 is a schematic block diagram of a rake receiver in a CDMA system.

FIG. 2 is a schematic block diagram of a G-RAKE receiver in a CDMAsystem.

FIG. 3 is a schematic block diagram of a rake receiver according to anembodiment of the present invention.

FIG. 4 is a flow chart showing the process steps of a de-spreadingmethod according to an embodiment of the present invention.

FIG. 5 is a flow chart showing the sub-steps of the Step S460 accordingto the embodiment of the present invention.

FIG. 6 is a trend chart of an error rate under different ratios betweenbit energy and noise energy E_(b)/N₀.

DESCRIPTION OF EMBODIMENTS

In order to overcome attenuation of the multi-path channel transmissionand to restrain colored Gaussian noises in the channel, recently aG-RAKE receiver is proposed to improve the performance of the receivingterminal and the bit error rate. However, the operation complexity ofthe receiving terminal is greatly enhanced, and a large number ofcalculations are required. Therefore, the rake receiver provided by thepresent invention can maintain the performance and bit error rate asequivalent to the G-RAKE receiver, and can effectively lower thecomplexity and reduce the calculations in the operation.

In order to clearly illustrate the implementing manner of the presentinvention, it is assumed that the rake receiver provided by the presentinvention is applied to a spread-spectrum system. That is to say, atransmitting terminal makes the signal to be transmitted be multipliedby a spreading sequence. The spreading system can be a direct sequencecode division multiple access (DS-CDMA) system and a wideband codedivision multiple access (W-CDMA) system, etc.

FIG. 3 is a systematic block diagram of a rake receiver according to anembodiment of the present invention. Referring to FIG. 3, a rakereceiver 300 includes a channel estimation module 305, signal branches310_0-310_(L−1), noise branches 320_0-320_(I−1), and a combiner 370, inwhich both L and I are positive integers. The channel estimation module305 estimates path delay times h₀-h_(L-1) and corresponding channelgains h₀-h_(L-1) for each path in the multi-path channel, and L is thenumber of the paths resolved by the channel estimation module 305. Inthis embodiment, how the channel estimation module 305 performs thechannel estimation is not illustrated, but those of ordinary skill inthe art shall know various channel estimation methods have beendeveloped in the current communication technology, and as long as thechannel estimation method is capable of estimating the path delay timesτ₀-τ_(L-1) and the corresponding channel gains h₀-h_(L-1) for each pathin the multi-path channel, it can be applied in the present invention.

Each signal branch 310_0-310_(L−1) in FIG. 3 includes a delay unit and ade-spreader. Taking the i^(th) signal branch 310 _(—) i as an example,it includes a delay unit 330 _(—) i and a de-spreader 340 _(—) i, inwhich i is an integer between 0−(L−1). In addition, each noise branch320_0-320_(I−1) also includes a delay unit and a de-spreaderrespectively. Taking the j^(th) noise branch 320 _(—) j as an example,it includes a delay unit 350 _(—) j and a de-spreader 360 _(—) j, inwhich j is an integer between 0−(I−1).

The delay units 330_0-330_(L−1) in the signal branches 310_0-310_(L−1)respectively have signal delay times l₀-l_(L-1) proportional to the pathdelay times τ₀-τ_(L-1) estimated by the channel estimation module 305.In this embodiment, the proportional relation there-between is 1. Thatis, the delay time l₀=τ₀, l₁=τ₁, . . . , l_(L-1)=τ_(L-1). In addition,the delay units 350_0-330_(I−1) in the noise branches 320_0-320_(I−1)respectively have preset times m₀-m_(I-1). How to determine the presettimes m₀-m_(I-1) is illustrated below in the latter part of thisembodiment in great detail.

The rake receiver 300 receives the received signal r(t) from themulti-path channel. The received signal r(t) is respectively input tothe signal branches 310_0-310_(L−1) and the noise branches320_0-320_(I−1). In this embodiment, after performing a similar processon the received signal r(t), each signal branch 310_0-310_(L−1) outputssignal components y_(s)(l₀)-y_(s)(l_(L-1)) respectively, so only theoperation within the signal branch 310_1 is illustrated below. First,the delay unit 330_1 delays the received signal r(t) for l₁, so as tooutput a delayed received signal r(t+l₁) to the de-spreader 340_1. Next,the de-spreader 340_1 convolves the delayed received signal r(t+l₁) witha spreading waveform, then samples the convolved result as a signalcomponent y_(s)(l₁) when the time t=l₁, and outputs the signal componenty_(s)(l₁) to the combiner 370. The spreading waveform is a convolutionof the local spreading sequence and the pulse shaping.

In this embodiment, after performing a similar process on the receivedsignal r(t), each noise branch 320_0-320_(I−1) outputs noise componentsy_(n)(m₀)-y_(n)(m_(I-1)), so only the operations within the signalbranch 320_1 is illustrated below. First, the delay unit 350_1 delaysthe received signal r(t) for a preset time m₁, so as to output a delayedreceived signal r(t+m₁) to the de-spreader 360_1. Next, the de-spreader360_1 convolves the delayed received signal r(t+m₁) with the spreadingwaveform, then samples the convolved result to a noise componenty_(n)(m₁) when the time t=m₁, and then outputs the noise componenty_(n)(m₁) to the combiner 370.

The combiner 370 includes a signal combining unit 371, a noise combiningunit 377, and an adder 382. After the combiner 370 receives the signalcomponents y_(s)(l₀)-y_(s)(l_(L-1)) and the noise componentsy_(n)(m₀)-y_(n)(m_(I-1)), the signal combining unit 371 combines thesignal components y_(s)(l₀)-y_(s)(l_(L-1)) according to differentweights so as to generate and output a main signal x. The noisecombining unit 377 combines the noise componentsy_(n)(m₀)-y_(n)(m_(I-1)) according to different weights, so as togenerate and output an interference-plus-noise estimation value{circumflex over (z)}. Finally, the adder 382 subtracts theinterference-plus-noise estimation value {circumflex over (z)} from themain signal x to obtain and output a de-spreading signal {circumflexover (x)}.

The signal combining unit 371 includes L multipliers 373_0-373_(L−1) anda summation unit 375. Each multiplier 373_0-373_(L−1) makes the receivedsignal components y_(s)(l₀)-y_(s)(l_(L-1)) be multiplied by thecorresponding signal weights A₀-A_(L-1), and outputs the obtainedproducts to the summation unit 375. After the summation unit 375 sums upthe products from the multipliers 373_0-373_(L−1), the sum is taken asthe main signal x, which is output to the adder 382. The signal weightsA₀-A_(L-1) are, for example, obtained by performing a specific operationon the channel gains h₀-h_(L-1) estimated by the channel estimationmodule 305, in which the specific operation can be conjugate of thechannel gains h₀-h_(L-1), or conjugate after multiplying the channelgains h₀-h_(L-1) by a constant or a function. In this embodiment, thespecific operation is, for example, conjugate of the channel gainsh₀-h_(L-1). Therefore, the signal weights A₀=h₀*, A₁=h₁*, . . . , andA_(L-1)=h_(L-1)*.

The noise combining unit 377 includes I multipliers 379_0-379_(I−1) anda summation unit 380. Each multiplier 379_0-379_(I−1) makes the receivednoise components y_(n)(m₀)-y_(n)(m_(I-1)) be multiplied by thecorresponding noise weights B₀-B_(I-1), and then outputs the obtainedproducts to the summation unit 380. The summation unit 380 sums up theproducts from the multipliers 379_0-379_(I−1), and takes the sum as theinterference-plus-noise estimation value Z for being output to the adder382. Here, in order to illustrate the content of the specification morefluently, how to obtain the noise weights B₀-B_(I-1) is not illustratedfor the moment. However, how to obtain the noise weights B₀-B_(I-1) sillustrated in the latter part of this embodiment in great detail.

It is known from the above embodiment that the signal delay timesl₀-l_(L-1) of the delay units 330_0-330_(L−1) in the signal branches310_0-310_(L−1) are generated according to the path delay timesτ₀-τ_(L-1) of the multi-path channel. The signal weights in the signalcombining unit 371 are generated according to the channel gainsh₀-h_(L-1) of the multi-path channel. That is, the signal branches310_0-310_(L−1) and the signal combining unit 371 are similar to therake receiver 100 of FIG. 1, and the generated main signal x collectsthe signal components on each path in the multi-path channel, so as toresist the attenuation of the signal caused by the multi-path channel.

Although the signal branches 310_0-310_(L−1) and the signal combiningunit 371 can overcome the attenuation of the multi-path channel, thegenerated main signal x still contains noises in the channel, and thenoises may be generated due to the ISI and MUI, such that the noises inthe channel are the colored Gaussian noise. The spirit of the presentinvention lies in utilizing the interference-plus-noise estimation valuez generated by the noise branches 320_0-320_(L−1) and the noisecombining unit 380 to eliminate the colored Gaussian noise in the mainsignal x.

The rake receiver 300 in the embodiment of the present invention furtherincludes a noise branch selecting unit 363 and a noise weightcalculating unit 366. The noise branch selecting unit 363 is used toselect the preset times m₀-m_(I-1) in the noise branches320_0-320_(L−1), and the noise weight calculating unit 366 is used togenerate the noise weights B₀-B_(I-1). It is respectively deduced belowhow the noise weight calculating unit 366 calculates the noise weightsB₀-B_(I-1), and how the noise branch selecting unit 363 selects thepreset times m₀-m_(I-1), such that the interference-plus-noiseestimation value {circumflex over (z)} output by the noise combiningunit 380 can be used to eliminate the noises in the main signal x.

First, in order to conveniently illustrate the following deductionprocess, several symbols are predefined. First, a signal weight vectorformed by the conjugate value of the plurality of signal weightsA₀-A_(L-1) is defined as α=[A₀*, . . . , A_(L-1)*]^(T), and a noiseweight vector formed by the conjugate value of the plurality of noiseweights B₀-B_(I-1) is defined as β=[B₀*, . . . , B_(I-1)*]^(T). Next,the main signal x generated by the signal branches 310_0-310_(L−1) andthe signal combining unit 371 further includes the noise in the channel,that is to say, the main signal x can be divided into a signal part anda noise part. Therefore, the noise part in the main signal x is definedas z_(α), and z_(α) has collected the noises in the signal componentsy_(s)(l₀)-y_(s)(l_(L-1)) output by each signal branch 310_0-310_(L−1),so z_(α) can be expressed as

z_(α)=α^(H)z_(s)  (2),

in which each element in the vector z_(s) respectively represents thenoises in the signal components y_(s)(l₀)-y_(s)(l_(L-1)).

Next, the noise components y_(n)(m₀)-y_(n)(m_(I-1)) output by the noisebranches 320_0-320_(I−1) are defined as a vector y _(n)=[y_(n)(m₀), . .. , y_(n)(m_(I-1))]^(T). Through the definitions of y _(n) and β, theinterference-plus-noise estimation value output by the noise combiningunit 377 is defined as {circumflex over (z)}=β^(H) y _(n). In addition,the noise branches 320_0-320_(I−1) in this embodiment are used tocollect the interference and noises in the channel, and the noisecomponents y_(n)(m₀)-y_(n)(m_(I-1)) output by the noise branches320_0-320_(I−1) does not contain any data component. Therefore, it isassumed therein that y _(n)≈z_(n), that is, it is assumed herein that y_(n) only includes the interference and the noise z _(n).

Finally, the signal components y_(s)(l₀)-y_(s)(l_(L-1)) output by thesignal branches 310_0-310_(L−1) are defined as a vectors y_(s)=[y_(s)(l₀), . . . , y_(s)(l_(L-1))]^(T). Through the definitions ofy _(s) and α, the main signal output by the signal combining unit 371 isdefined as x=α^(H) y _(s). The de-spreading signal {circumflex over (x)}output by the adder 382 can be expressed as:

{circumflex over (x)}=x−{circumflex over (z)}=α ^(H) y _(s)−β^(H) y_(n)  (3).

Hereinafter, the deduction of the noise weights B₀-B_(I-1) may bedescribed as follows.

First, the interference-plus-noise estimation value {circumflex over(z)} output by the noise combining unit 377 is expected to eliminate thenoise part z_(α) in the main signal x, and thus, according to theminimum mean-square error (MMSE) principle, it is necessary for theinterference-plus-noise estimation value {circumflex over (z)} tominimize E[|{circumflex over (z)}−z_(α)|²], wherein E[•] represents theexpected value operation.

Next, the interference-plus-noise estimation value {circumflex over(z)}=β^(H) y _(n) is substituted into min

E[|{circumflex over (z)}−z_(α)|²]

, and a Wiener-Hopf equation is used to acquire a noise weight vector:

β=E[y _(n) y _(n) ^(H)]⁻¹ E[y _(n) z _(α)*]  (4).

From Equation (2) and y _(n)≈z _(n), Equation (3) is converted to:

β=E[z _(n) z _(n) ^(H)]⁻¹E[z _(n) z _(s) ^(H)]α  (5).

The correlation matrix E[z _(n) z _(s) ^(H)] is defined as matrix R_(ns)and the auto correlation matrix E[z _(n) z _(n) ^(H)] is defined asmatrix R_(n), and Equation (5) is converted to:

β=R_(n) ⁻¹R_(ns)α  (6).

According to Equation (6), the value of each element in β can bededuced, so as to further acquire the noise weights B₀-B_(I-1).

In the above illustration, it is not illustrated how to obtain thematrices R_(ns) and R_(n). However, the matrices R_(ns) and R_(n) areobtained from a noise matrix R_(u). Furthermore, the method ofcalculating each element in the matrix R_(u) has been illustratedthrough Equations (6), (7), and (8) in the document of Note [1] andEquations (25), (26), and (27) in the document of Note [2]. In addition,in the documents of Note [1] and Note [2], R_(u) is defined as thecovariance matrix of the noise vector u, and the noise matrix R_(u) canbe expressed as

R_(u)=E[uu^(H)]  (7),

in which the element in the noise vector u is the noise in the signaloutput by each finger in the G-RAKE receiver.

Here, if the signal branches 310_0-310_(L−1) and the noise branches320_0-320_(L−1) in the rake receiver 300 in this embodiment areconsidered as the fingers of the G-RAKE receiver, and the noise vector ucan be considered as the concatenation of z_(s) and z _(n). That is, thenoise u can be expressed as:

$\begin{matrix}{\underset{\_}{u} = {\begin{bmatrix}{\underset{\_}{z}}_{s} \\{\underset{\_}{z}}_{n}\end{bmatrix}.}} & (8)\end{matrix}$

The Equation (8) is substituted into Equation (7) to obtain:

$\begin{matrix}\begin{matrix}{{\underset{\_}{R}}_{u} = {E\left\lbrack {\begin{bmatrix}{\underset{\_}{z}}_{s} \\{\underset{\_}{z}}_{n}\end{bmatrix}\begin{bmatrix}{\underset{\_}{z}}_{s}^{H} & {\underset{\_}{z}}_{n}^{H}\end{bmatrix}} \right\rbrack}} \\{= {\begin{bmatrix}{E\left\lbrack {{\underset{\_}{z}}_{s}{\underset{\_}{z}}_{s}^{H}} \right\rbrack} & {E\left\lbrack {{\underset{\_}{z}}_{s}{\underset{\_}{z}}_{n}^{H}} \right\rbrack} \\{E\left\lbrack {{\underset{\_}{z}}_{n}{\underset{\_}{z}}_{s}^{H}} \right\rbrack} & {E\left\lbrack {{\underset{\_}{z}}_{n}{\underset{\_}{z}}_{n}^{H}} \right\rbrack}\end{bmatrix}.}}\end{matrix} & (9)\end{matrix}$

As viewed from Equation (9), it can be known that, the sub-matrixes E[z_(n)z_(s) ^(H)] and E[z _(n) z _(n) ^(H)] in the noise matrix R_(u)provided in the documents of Note [1] and Note [2] are respectively thedefined matrixes R_(ns) and R_(n). The dimension of the noise matrixR_(u) is (L+I)×(L+I), the matrix R_(n) is the I×I sub-matrix at thebottom right corner of the noise matrix R_(u), and the matrix R_(ns) isthe I×L sub-matrix at the bottom right corner of the noise matrix R_(u).

In other words, the noise weight calculating unit 366 in the embodimentof the present invention only needs to calculate a part of the elementsin the noise matrix R_(u) so as to obtain the matrices R_(ns) and R_(n),then calculate the inverse matrix R_(n) ⁻¹ of the matrix R_(n), and thensubstitute the matrixes R_(ns) and R_(n) ⁻¹ into Equation (6) to obtainthe value of each element in β, thereby further obtain the noise weightsB₀-B_(I-1).

It is known from the above process of determining the noise weightsB₀-B_(I-1) that, compared to the conventional G-RAKE receiver, the rakereceiver provided by the present invention only needs to calculate apart of the elements in the matrix R_(u). Furthermore, the rake receiverprovided by the present invention only needs to calculate the inversematrix of the matrix R_(n) with the dimension of I×I, instead ofcalculating the inverse matrix of the noise matrix R_(u) with thedimension of J×J, in which I is the number of the noise branches, and Jis the number of all the branches, i.e., the number of noise branchesand the number of the signal branches (L+I). Therefore, the rakereceiver in this embodiment significantly reduces the calculations andthe complexity required for generating the weights compared with theconventional G-RAKE receiver.

The signal branches 310_0-310_(L−1) of the rake receiver 300 in thisembodiment are set to be used for collecting signals in each path. Thenoise branches 320_0-320_(I−1) are set to be used for eliminating theremainder interference and noises in the main signal x. Therefore, thepreset times m₀-m_(I-1) in the noise branches 320_0-320_(I−1) aredetermined by maximization of the signal to interference plus noiseratio (SINR) of the de-spreading signal {circumflex over (x)} inprinciple. It is deduced below how the noise branch selecting unit 363allocates the preset times m₀-m_(I-1).

It is known from Equation (3) that, the de-spreading signal is{circumflex over (x)}=α^(H) y _(s)−β^(H) y _(n), and the interferenceplus noise energy in {circumflex over (x)} is E[|α^(H)z_(s)−β^(H) z_(n)|²], and can be decomposed as:

E[|α ^(H) z _(s)−β^(H) z _(n)|² ]=E[|z _(α)|²]−α^(H) R _(ns) ^(H) R _(n)⁻¹ R _(ns)α  (10).

The signal components in the de-spreading signal {circumflex over (x)}are all provided by the signal branches 310_1-310_(L−1), which isindependent of the noise branches 320_0-320_(I−1). Therefore, themaximizing of the SINR of the de-spreading signal {circumflex over (x)}is equivalent to maximizing of α^(H)R_(ns) ^(H)R_(n) ⁻¹R_(ns)α a inEquation (10).

Herein, it is assumed that there are J candidates of the preset times,and the noise branch selecting unit 363 must select I preset times. Jcandidates can be determined according to the maximum path delay timeestimated by the channel estimating unit or the hardware architecture ofthe receiver. I preset times yield C_(I) ^(J)=J!/I!(J−I)! kinds ofdifferent selections, that is, J!I!(J−I)! combinations of differentpreset times. According to Equation (10), after calculating theinterference plus noise energy E[|α^(H)z_(s)−β^(H) z _(n)|²] generatedin each selecting mode, a certain combination of I preset times thatachieves the minimum interference plus noise energy E[|α^(H)z_(s)−β^(H)z _(n)|²] of the de-spreading signal {circumflex over (x)} is found out.

However, all the J!/I!(J−I)! kinds of combinations of different presettimes require the calculation of α^(H)R_(ns) ^(H)R_(n) ⁻¹R_(ns)α inEquation (10). During the calculation process, the calculations of theinverse matrix of R_(n) and the matrix multiplication are required.Therefore, the process of selecting the preset times m₀-m_(I-1) willresult in large number of operations for the rake receiver. In order tolower the operations and to avoid calculations of matrix inversion andmatrix multiplication, merely the effects of individual candidates onthe elimination of the interference and the noise are considered in theembodiment of the present invention, and the first I candidates capableof effectively eliminating the interference are selected.

First, a candidate is taken as the preset time m_(i) of a noise branchherein, and it is assumed that only this noise branch exists at thistime, and thus, Equation (10) is simplified as:

E[|α ^(H) z _(s)−β^(H) z _(n)|² ]=E[|α ^(H) z _(s)−{tilde over (β)}_(i)z _(n)(m _(i))|²]  (11),

in which β_(i)* is the noise weight corresponding to the noise branch,and z_(n)(m_(i)) is the output of the noise branch. From β obtained inEquation (5), the noise weight when only one noise branch exists isobtained as:

$\begin{matrix}{\beta_{i} = {\frac{{E\left\lbrack {{\underset{\_}{z}}_{s}^{H}{z_{n}\left( m_{i} \right)}} \right\rbrack}\underset{\_}{\alpha}}{E\left\lbrack {{z_{n}\left( m_{i} \right)}}^{2} \right\rbrack}.}} & (12)\end{matrix}$

After expanding Equation (11), the interference plus noise energy can beobtained as:

E[|α ^(H) z _(s)−β^(H) z _(n)|² ]=E[|z _(α)|²]−|β_(i)|² E[|z _(n)(m_(i))|²]  (13),

in which z_(α) is the noise part of the main signal x in the abovedefinition, and is independent of the preset time selection in the noisebranch. Therefore, in the process of selecting the preset timesm₀-m_(I-1) by the noise branch selecting unit 363, merely a metriccorresponding to each candidate needs to be calculated, so as to findthe first I candidates having relatively large metrics to serve as thepreset times m₀-m_(I-1). The metric is, for example,|β_(i)|²E[|z_(n)(m_(i))|²] in Equation (13). In other words, the noisebranch selecting unit 363 only needs to calculate the metric|β_(i)|²E[|z_(n)(m_(i))|²] of each candidate, and it is not necessary tocalculate the inverse matrix of R_(n) and the matrix multiplication, sothat the calculations required when selecting the preset time arereduced.

According to the above rake receiver 300, a de-spreading method can beconcluded. FIG. 4 is a flow chart showing the process steps of ade-spreading method according to an embodiment of the present invention.Referring to FIGS. 3 and 4, first, the channel estimation module 305estimates the channel gains h₀-h_(L-1) and the corresponding path delaytimes τ₀-τ_(L-1) in the multi-path channel (Step S405). Next, the rakereceiver 300 receives the received signal r(t) from the multi-pathchannel, and the received signal r(t) is input to the signal branches310_0-310_(L−1) and the noise branches 320_0-320_(I−1) (Step S410).Next, the delay units 330_0-330_(L−1) in the signal branches310_0-310_(L−1) respectively delay the received signal r(t) for a signaldelay time l₀-l_(L-1), so as to obtain the delayed received signalsr(t+l₁)-r(t+l_(L-1)) (Step S415), and the de-spreaders 340_0-340_(L−1)in the signal branches 310_0-310_(L−1) respectively convolve the delayedreceived signals r(t+l₀)-r(t+l_(L-1)) with the local spreading waveform,and respectively sample the convolved results to the signal componentsy_(s)(l₀)-y_(s)(l_(L-1)) (Step S420).

Then, among the plurality of candidates, the noise branch selecting unit363 calculates the metric |β_(i)|²E[|z_(n)(m_(i))|²] of each candidate(Step S425), and selects the first I candidates having relatively largemetrics as the preset times m₀-m_(I-1) (Step S430).

Next, the delay units 350_0-350_(I−1) in the noise branches320_0-320_(I−1) respectively delay the received signal r(t) for a presettime m₀-m_(I-1), so as to obtain the delayed noise signalsr(t+m₀)-r(t+m_(I-1),) (Step S435). The de-spreaders 360_0-360_(I−1) inthe noise branches 320_0-320_(I−1) respectively convolve the delayednoise signals r(t+m₀)-r(t+m_(I-1)) with a local spreading waveform, andrespectively sample the convolved results as the noise componentsy_(n)(m₀)-y_(n)(m_(I-1)) (Step S440).

After the signal combining unit 371 receives the signal componentsy_(s)(l₀)-y_(s)(l_(I-1)), the multipliers 373_0-373_(L−1) in the signalcombining unit 371 make the signal components y_(s)(l₀)-y_(s)(l_(L-1))be multiplied by the corresponding signal weights A₀-A_(L-1), and outputthe generated products to the summation unit 375 (Step S445). Thesummation unit 375 sums up the received products, so as to obtain themain signal x (Step S450).

Next, the noise weight generating unit 366 generates a plurality ofnoise weights B₀-B_(I-1) (Step S460). In this embodiment, Step S460further includes a plurality of sub-steps as shown in FIG. 5. Referringto FIG. 5, firstly, a I×I sub-matrix at the bottom right corner of thenoise matrix R_(u) is calculated, so as to obtain the matrix R_(n) (StepS462). Next, a I×L sub-matrix at the bottom left corner of the noisematrix R_(u) is calculated, so as to obtain the matrix R_(ns) (StepS464). The noise vector u includes the noises of the signal output byeach signal branch and each noise branch, and has a length of I+L. R_(u)is the covariance matrix of the noise vector u, and has the dimension of(I+L)×(I+L). In addition, in the documents of Note [1] and Note [2], themethod of calculating each element in the noise matrix R_(u) has beendisclosed. Next, the inverse matrix of the matrix R_(n) is calculated,so as to obtain the matrix R_(n) ⁻¹ (Step S466). Finally, the noiseweights B₀-B_(I-1) is calculated according to the equation β=R_(n)⁻¹R_(ns)α (Step S468).

Referring to FIGS. 3 and 4 again, after the noise weights B₀-B_(I-1) aregenerated, the multipliers 379_0-379_(I−1) in the noise combining unit377 make the noise components y_(n)(m₀)-y_(n)(m_(I-1)) be multiplied bythe corresponding noise weights B₀-B_(I-1) and output the generatedproducts to the summation unit 380 (Step S470). Then, the summation unit380 sums up the received products, so as to obtain theinterference-plus-noise estimation value {circumflex over (z)} (StepS475). Finally, the adder 382 subtracts the interference-plus-noiseestimation value {circumflex over (z)} from the main signal x to obtainand output a de-spreading signal {circumflex over (x)} (Step S480).

The performances of the conventional rake receiver, the G-RAKE receiver,and the rake receiver in the embodiment of the present invention aresimulated below through software, and it is assumed that the abovesimulation employs a multi-path Rayleigh fading channel. Spreadingfactor used by the system is 128, and the number of the multiple usersis 32. FIG. 6 is a trend chart of an error rate under different ratiosbetween bit energy and noise energy E_(b)/N₀. Referring to FIG. 6, theX-coordinate is the ratio of the bit energy to the noise energy E_(b)/N₀with a unit of dB, and the Y-coordinate is the bit error rate. Fivecurves in FIG. 6 respectively represent the conventional rake receiver(the rake receiver in FIG. 1), the G-RAKE receiver (having two noisebranches, that is, the delay time in the two noise branches are not thedelay time the channel), the rake receiver in the embodiment of thepresent invention (having two noise branches), the G-RAKE receiver(having four noise branches, that is, the delay time in the four noisebranches are not the delay time in the channel), and the rake receiverin the embodiment of the present invention (having four noise branches).In addition, the simulation environment of FIG. 6 is a multi-pathchannel having four paths, and the receivers simulated by the fivecurves of FIG. 6 all have four signal branches.

As viewed from FIG. 6 that, the bit error rate of the rake receiver inthe embodiment of the present invention is significantly smaller thanthat of the conventional rake receiver. In addition, the bit error rateof the rake receiver in the embodiment of the present invention is quiteclose to that of the G-RAKE receiver. However, taking the G-RAKEreceiver having four noise branches as an example, an 8*8 inverse matrixmust be calculated, and as for the rake receiver having four noisebranches according to the embodiment of the present invention only needsto calculate a 4*4 inverse matrix. Therefore, the rake receiver in theembodiment of the present invention can maintain the bit error rateequivalent to that of the G-RAKE receiver, and can also significantlyreduce the operations required by the G_RAKE receiver.

To sum up, the embodiment of the present invention has the followingadvantages.

1. The rake receiver according to the embodiment of the presentinvention uses an interference-plus-noise estimation value to eliminatethe noises in the main signal, so as to effectively improve theperformance of the receiver and lower the bit error rate.

2. When calculating the noise weights, the conventional G-RAKE receiverneeds to calculate the inverse matrix operation on the matrix R_(u) witha dimension of J×J. However, when the rake receiver according to theembodiment of the present invention calculates the weights, it is onlyrequired to calculate the inverse matrix of the I×I sub-matrix R_(n) inthe matrix R_(u). Therefore, the rake receiver according to theembodiment of the present invention can significantly reduce theoperations required by the G-RAKE receiver.

3. When the rake receiver according to the embodiment of the presentinvention selects the preset times in the noise branches, merely themetric |β_(i)|²E[|z_(n)(m_(i))|²] corresponding to each candidate needsto be calculated, and it is not necessary to calculate the inversematrix of R_(n) and the matrix multiplication, so as to reduce thecalculations required when selecting the preset times.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the structure of the presentinvention without departing from the scope or spirit of the invention.In view of the foregoing, it is intended that the present inventioncover modifications and variations of this invention provided they fallwithin the scope of the following claims and their equivalents.

1. A rake receiver, adapted for de-spreading a received signal from amulti-path channel, comprising: a channel estimation module, forestimating a plurality of channel gains and a plurality of correspondingpath delay times in the multi-path channel; L signal branches, fordelaying the received signal for a plurality of signal delay timesrespectively to obtain a plurality of delayed received signals,de-spreading the delayed received signals respectively to output aplurality of signal components, wherein the signal delay times arerespectively proportional to the path delay times, and L is a positiveinteger; I noise branches, for delaying the received signal for aplurality of preset times respectively to obtain a plurality of delayednoise signals, de-spreading the delayed noise signals to output aplurality of noise components respectively, wherein I is a positiveinteger; and a combiner, for combining the signal components to generatea main signal, combining the noise components to generate aninterference-plus-noise estimation value, and outputting a de-spreadingsignal according to a difference between the main signal and theinterference-plus-noise estimation value; wherein the combiner adjustsweights of the signal components in the main signal according to thechannel gains, and adjusts weights of the noise components in theinterference-plus-noise estimation value according to I noise weights.2. The rake receiver as claimed in claim 1, wherein an i^(th) signalbranch among the L signal branches comprises: a delay unit, for delayingthe received signal for an i^(th) signal delay time to obtain an i^(th)delayed received signal; and a de-spreader, for convolving the i^(th)delayed received signal with a local spreading waveform, and samplingthe convolved result to an i^(th) signal component.
 3. The rake receiveras claimed in claim 1, wherein an i^(th) noise branch among the I noisebranches comprises: a delay unit, for delaying the received signal foran i^(th) preset time to obtain an i^(th) delayed noise signal; and ade-spreader, for convolving the i^(th) delayed noise signal with a localspreading waveform, and sampling the convolved result to an i^(th) noisecomponent.
 4. The rake receiver as claimed in claim 1, wherein thecombiner comprises: a signal combining unit, for combining the signalcomponents according to L signal weights to generate and output the mainsignal, wherein the signal weights are obtained by the channel gains ofthe multi-path channel; a noise combining unit, for combining the signalcomponents according to I signal weights to generate and output theinterference-plus-noise estimation value; and an adder, subtracting theinterference-plus-noise estimation value from the main signal, so as tooutput the de-spreading signal.
 5. The rake receiver as claimed in claim4, wherein the signal combining unit comprises: L multipliers, whereinan i^(th) multiplier receives an i^(th) signal component, and multipliesthe i^(th) signal component by an i^(th) signal weight, so as to outputan i^(th) product; and a summation unit, for receiving and summing upthe products to output the main signal.
 6. The rake receiver as claimedin claim 4, wherein the noise combining unit comprises: I multipliers,wherein an i^(th) multiplier receives an i^(th) noise component, andmultiplies the i^(th) noise component by an i^(th) noise weight, so asto output an i^(th) product; and a summation unit, for receiving andsumming up the products to output the interference-plus-noise estimationvalue.
 7. The rake receiver as claimed in claim 6, wherein the signalweights are represented as A₀-A_(L-1), and a signal weight vector formedby the conjugate value of the signal weights A₀-A_(L-1) is representedas α=[A₀*, . . . , A_(L-1)*]^(T); the noise weights are represented asB₀-B_(I-1), and a noise weight vector formed by the conjugate value ofthe noise weights B₀-B_(I-1) is represented as β=[B₀*, . . . ,B_(I-1)]^(T), and the rake receiver further comprises: a noise weightcalculating unit, for calculating the noise weights B₀-B_(I-1) through anoise matrix R_(u) and an equation β=R_(n) ⁻R_(ns)α, and outputting thenoise weights B₀-B_(I-1) to the noise combining unit, wherein the noisematrix R_(u) is a covariance matrix of a noise vector u, with adimension of (I+L)×(I+L), the noise vector u comprises noisecompositions in the signals components and the noise components, with alength of I+L, the matrix R_(n) is a I×I sub-matrix at a bottom rightcorner of the noise matrix R_(u), the matrix R_(ns) is a I×L sub-matrixat a bottom left corner of the noise matrix R_(u), and the superscript(−1) represents an inverse matrix operation.
 8. The rake receiver asclaimed in claim 7, further comprising: a noise branch selecting unit,for selecting first I candidates having larger metrics from a pluralityof candidates, so as to serve as the preset times, wherein the metric is|β_(i)|²E[|z_(n)(m_(i))|²], the i^(th) candidate corresponds to thei^(th) preset time m_(i), the i^(th) noise branch generates the i^(th)noise component z_(n)(m_(i)) according to the i^(th) preset time m_(i),β_(i) is a conjugate value of the noise weight corresponding to thei^(th) noise component z_(n)(m_(i)), and E[•] represents an expectedvalue operation.
 9. A de-spreading method used for a rake receiver,comprising: estimating a plurality of channel gains and a plurality ofcorresponding path delay times in a multi-path channel; receiving areceived signal from the multi-path channel; delaying the receivedsignal for a plurality of signal delay times respectively to obtain aplurality of delayed received signals, de-spreading the delayed receivedsignals respectively to obtain a plurality of signal components, whereinthe signal delay times are respectively proportional to the path delaytimes; delaying the received signal for a plurality of preset timesrespectively to obtain a plurality of delayed noise signals,de-spreading the delayed noise signals respectively to obtain aplurality of noise components; adjusting weights of the signalcomponents in a main signal respectively according to the channel gains,so as to combine the signal components to obtain the main signal;adjusting weights of the noise components in an interference-plus-noiseestimation value according to a plurality of noise weights, so as tocombine the noise components to obtain the interference-plus-noiseestimation value; and generating a de-spreading signal according to adifference between the main signal and the interference-plus-noiseestimation value.
 10. The de-spreading method as claimed in claim 9,wherein the step of generating the signal components comprises: delayingthe received signal for an i^(th) signal delay time to obtain an i^(th)delayed received signal; and convolving the i^(th) delayed receivedsignal with a local spreading waveform, and sampling the convolvedresult to an i^(th) signal component.
 11. The de-spreading method asclaimed in claim 9, wherein the step of generating the noise componentscomprises: delaying the received signal for an i^(th) preset time toobtain an i^(th) delayed noise signal; and convolving the i^(th) delayednoise signal with a local spreading waveform, and sampling the convolvedresult to an i^(th) noise component.
 12. The de-spreading method asclaimed in claim 9, wherein the step of adjusting weights of the signalcomponents in a main signal respectively according to the channel gainsso as to combine the signal components to obtain the main signalcomprises: generating a plurality of signal weights according to thechannel gains; multiplying the i^(th) signal component by an i^(th)signal weight, so as to generate an i^(th) product; and summing up theproducts to obtain the main signal.
 13. The de-spreading method asclaimed in claim 12, wherein the step of adjusting weights of the noisecomponents in an interference-plus-noise estimation value according to aplurality of noise weights so as to combine the noise components toobtain the interference-plus-noise estimation value comprises:multiplying an i^(th) noise component by an i^(th) noise weight togenerate an i^(th) product; and summing up the products to obtain theinterference-plus-noise estimation value.
 14. The de-spreading method asclaimed in claim 13, wherein a number of the signal components is L, anumber of the noise components is I, the signal weights are representedas A₀-A_(L-1), and a signal weight vector formed by a conjugate value ofthe signal weights A₀-A_(L-1) is represented as α=[A₀*, . . . ,A_(L-1)]^(T),the noise weights are represented as B₀-B_(I-1), and anoise weight vector formed by a conjugate value of the noise weightsB₀-B_(I-1) is represented as β=[B₀*, . . . , B_(I-1)*]^(T), thede-spreading method further comprises: calculating a I×I sub-matrix at abottom right corner of a noise matrix R_(u) to obtain a matrix R_(n),wherein the noise matrix R_(u) is a covariance matrix of a noise vectoru, with a dimension of (I+L)×(I+L), and the noise vector u comprisesnoise compositions in the signals components and the noise components,with a length of I+L; calculating a I×L sub-matrix at a bottom leftcorner of the noise matrix R_(u) to obtain a matrix R_(ns); calculatingan inverse matrix of the matrix R_(n) to obtain a matrix R_(n) ⁻¹,wherein the superscript (−1) represents an inverse matrix operation; andcalculating the noise weights B₀-B_(I-1) according to an equationβ=R_(n) ⁻¹R_(ns)α.
 15. The de-spreading method as claimed in claim 14,further comprising: calculating a metric of an i^(th) candidate among aplurality of candidates; and selecting first I candidates having largermetrics to serve as the preset times, wherein the metric is|β_(i)|²E[|z_(n)(m_(i))|²], the i^(th) candidate corresponds to thei^(th) preset time m_(i), the i^(th) preset time m_(i) corresponds tothe i^(th) noise component z_(n)(m_(i)), β_(i) is a conjugate value ofthe noise weight corresponding to the i^(th) noise component, and E[•]represents an expected value operation.